Currently the control of prestressing force and cracks on concrete structures is designed deterministically. However, the statistical variations of materials could make additional error in the prediction and the control of errors. Therefore, to develop a probabilistic risk assessment technique in Prestressed Concrete (PSC) box girder railway bridges, the important random variables are determined by an Analytical Hierarchy Process (AHP) method for the risk assessment of the target PSC box girder bridge constructed by a Movable Scaffolding System (MSS) method. The limit state functions are determined to investigate the risk of tensile cracks in upper and lower flange concrete, just after the moving of scaffolding, and the risks of the prestressing loss at each construction stage. In order to compose the implicit limit state function of the target PSC railway bridge, the developed linear adaptive weighted response surface method combined with a first order second moment method is applied for the evaluation of reliabilities of the considered limit states.

Background: A quantitative model was developed and applied for analyzing the correlation between hydrogen-induced corrosion cracking in both main cable wires and degraded stiffening of the girders of a cable suspension bridge, considering maintenance effects across time and space. Method: Bayesian inference is applied for predicting the correlations among the wires in the main cables owed to hydrogen-induced cracking (HIC) in the cable wires of a steel bridge, by using the improved hierarchical Bayesian models proposed here. Results: The simulated risk prediction under decreased strength of cable wires, due to the corrosion cracking, yields posterior distributions based on prior distributions and likelihoods. The Bayesian inference model can be applied to the design and maintenance of highly corroded and correlated components Data are updated through analyzed information from previous crack steps. A numerical example including not only reliability indices but also probabilities of failure for cable wires, damaged by HIC, is then presented. Compared with a conventional linear prediction model, the one herein developed provides highly improved convergence and closeness to the analyzed data. Conclusion: The proposed model can be used as a diagnostic or prognostic prediction tool for the performance of corroded bridge cable wires with crack propagation, allowing the development of maintenance plans for mechanical components and the overall structural system.

Imaging devices of less than 300,000 pixels are mostly used for sewage conduit exploration due to the petty nature of the survey industry in Korea. Particularly, devices of less than 100,000 pixels are still widely used, and the environment for image processing is very dim. Since the sewage conduit images covered in this study have a very low resolution (240 × 320 = 76,800 pixels), it is very difficult to detect cracks. Because most of the resolutions of the sewer conduit images are very low in Korea, this problem of low resolution was selected as the subject of this study. Cracks were detected through a total of six steps of improving the crack in Step 2, finding the optimal threshold value in Step 3, and applying an algorithm to detect cracks in Step 5. Cracks were effectively detected by the optimal parameters in Steps 2 and 3 and the user algorithm in Step 5. Despite the very low resolution, the cracked images showed a 96.4% accuracy of detection, and the non-cracked images showed 94.5% accuracy. Moreover, the analysis was excellent in quality. It is believed that the findings of this study can be effectively used for crack detection with low-resolution images.